Perspectives on the Future of Ethiopia’s Agriculture: Land Constraints and Economy-Wide Analyses

1. ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Perspectives on the
Future of Ethiopia’s Agriculture:
Land Constraints and Economy-Wide Analyses
Emily Schmidt and Tim Thomas (Land Analysis)
Paul Dorosh, James Thurlow, Frehiwot Worku Kebede, Tadele Ferede
and Alemayehu Seyoum Taffesse (Economy-Wide Analysis)
Ethiopian Economics Association
15th International Conference on the Ethiopian Economy
July 20-22, 2017
Addis Ababa

2. Introduction
• Agricultural sector performance:
• Substantial public investments, technical change and output growth
• Spatial and structural transformation
• Urban population more than doubled in 20 years from 7.3 million in
1994 to 16.7 million in 2014
• Shares of agriculture in employment and GDP have fallen
• Dramatic improvement in household welfare:
• Rural poverty fell from 45 in 1999/00 to 30 percent in 2010/11
• Child malnutrition (stunting) fell from 58 to 40 percent from 2000 to
2014.
• Looking forward, how can this progress be sustained and even
accelerated?
2

3. • Recent Agricultural Performance: Can Rapid Growth Continue?
• Land Constraints: A GIS Analysis
• Future Scenarios: Drivers of Change
• Economy-wide Analysis: Simulation Results
• Next Steps
Plan of Presentation
3

4. • Increasingly binding land and water constraints (esp. in highlands)
• Technology-driven yield increases (improved seeds, quantity and
quality of fertilizer)
• Modernized value-chains (larger share marketed, reduced transport
costs, cold-chains, value-addition)
• Decelerating demand for cereals – accelerating demand for meat,
dairy and process goods
• Faster urbanization
• Public investments: road and port infrastructure, urban versus rural
• International economic climate and foreign investment
Drivers of Transformation
4

5. -1
1
3
5
7
9
11 2005/06
2006/07
2007/08
2008/09
2009/10
2010/11
2011/12
2012/13
2013/14
2014/15
2015/16
Percent
Area Yield
Source: Calculated from CSA Agricultural Sample Survey data. (Adapted from Bachewe
et al., 2017).
Annual Growth in Cereal Area
Cultivated and Yield, 2004/05 – 2015/16
5

6. a Not including 2014/15.
Note: Other factors (pesticides, irrigation, extension, services, returns to scale
and rural roads) are not shown.
Source: Calculated from CSA Agricultural Sample Survey data. (Adapted from Bachewe
et al., 2017).
TFP Growth in Crop Agriculture Has Slowed
6
Year
Change
in output
(∆Q/Q)
Land Labor Fertilizer
Improved
seeds
∆ TFP
Growth Rate of Factors
2004/05-2015/16a
8.27 2.59 3.62 10.58 11.09 2.02
2010/11-2015/16a
6.70 1.82 2.89 12.72 6.13 0.85

7. • Defines land cover types over the earth’s surface at a 500 meter resolution
derived from observations spanning a year’s input of Terra- and Aqua-
MODIS data
• Covers time period between 2001 and 2013
– To reduce noise in satellite data (cloud cover, variations in annual
rainfall, etc.), we average over 3 time periods: 2001-2004; 2005-2009;
2010-2013
• Identifies 17 land cover classes: 5 forest classes, shrub lands, savanna,
grassland, cropland, vegetation mosaic, urban, water, snow/ice, barren
– To estimate total crop area, we use the sum of cropland and 50% of
vegetation mosaic.
Friedl, M. A., Sulla-Menashe, D., Tan, B., Schneider, A., Ramankutty, N., Sibley, A., and Huang, X.
(2010). MODIS Collection 5 global land cover: Algorithm refinements and characterization of new
datasets. Remote Sensing of Environment, 114, 168–182
MODIS Land Cover Satellite Data
7

8. Source: Calculated from MODIS Land Cover Satellite Data.
Percentage Point Change in Cropland Area:
2005-09 to 2010-13
8
• Cropland expansion occurred
in:
• Kebeles surrounding
Addis Ababa
• Kebeles along the Addis
Ababa – Dire Dawa
corridor
• Eastern Tigray
• Cropland contracted:
• Eastern Amhara
• Western Tigray

9. Percentage of Kebeles with declines of 6% or more
Tigray SNNP Amhara Oromiya Other Total
2001-04 to 2005-09 34.2% 17.2% 11.4% 18.0% 9.2% 16.7%
2005-09 to 2009-13 17.3% 24.7% 23.1% 11.6% 3.9% 17.1%
2001-04 to 2009-13 24.3% 22.5% 11.3% 12.0% 7.7% 14.7%
Average Annual Growth in Crop Area
2001-04 to 2005-09 2.7% 1.2% 3.9% 2.1% -1.5% 2.7%
2005-09 to 2009-13 0.1% -1.1% 0.8% 3.2% 4.0% 1.2%
2001-04 to 2009-13 1.2% 0.0% 2.1% 2.3% 1.1% 1.8%
Total 2001-13 11.6% 0.3% 20.3% 23.2% 10.3% 17.0%
Ethiopia: Changes in Crop Area
2001-04 to 2009-13
Source: Calculated from NASA satellite data.
Land Expansion Appears to be Slowing Down
9

10. Change in cropshare (∆𝐶) is a function of:
• Area cropped in the base period (𝐶) and area cropped
squared (𝐶2)
• Vector of bioeconomic factors (𝑋), such as share of cropland
in base period, rainfall, elevation, terrain roughness (slope),
market access...
• Error term (𝜖)
∆𝐶 = 𝛼1 𝐶 + 𝛼2 𝐶2 + 𝛽𝑋 + 𝜖
• We also control for potential spatial dependence that may be
present in the initial OLS estimates (spatial error and spatial lag)
Land Use Changes: Econometric Analysis
10

11. • Initial share of cropland:
– The rate at which cropped area expands (across Ethiopia)
increases until approximately 25% of the kebele area is
being cropped.
• Access to markets:
– The farther a kebele is from town, the lower the
probability of converting to cropland.
• Improvements in road infrastructure:
– For each hour reduction in travel time to a city of 20k, the
probability of increasing agricultural area increases by 0.2
percent (highlands) and 0.4 percent (lowlands)
Factors Associated
with Expansion of Cropland
11

12. Source: Calculated from MODIS Land Cover Satellite Data.
Average Cropped Area: 2010-13
12
• The majority of cropped
area is in the highlands.
• A large share of kebeles
in Amhara region have
greater than 60 percent
of their total area in
cropland
• The lowland areas of
Ethiopia have little
cropped area

13. Source: Calculated from MODIS Land Cover Satellite Data.
Maximum Potential Cropped area
13
• Greater potential
cropped area exists in the
highlands, controlling for
biophysical
characteristics.
• Agricultural potential does
exist in the lowlands with
certain areas able to
attain cropped area of at
least 50% of total area.
• Maximum cropland expansion for each kebele is calculated by setting change in
cropland to zero and solving for C: ∆𝐶 = 0 = 𝛼1 𝐶 + 𝛼2 𝐶2 + 𝛽𝑋 + 𝜖

14. Source: Calculated from MODIS Land Cover Satellite Data.
Area Expansion Potential
14
• Although the highlands
has greater potential for
cropped area, there is
little area to expand
• Large share of Amhara
region has negative
potential to expand – and
in fact is / will contract
• Future cropped area
expansion is possible in
the lowlands
• Maximum cropland expansion for each kebele is calculated by setting change in
cropland to zero and solving for C: ∆𝐶 = 0 = 𝛼1 𝐶 + 𝛼2 𝐶2 + 𝛽𝑋 + 𝜖

15. • Satellite data analysis suggests that agricultural area expansion
in the highlands is reaching its maximum [economic] potential
(especially in the drought-prone highland areas)
• In this context, a regionally differentiated growth strategy is
needed:
– Agricultural intensification in the highlands: promoting
technology adoption for improved yields; more attention to
sustainable land management
– Area expansion in the lowland areas of Ethiopia: investing
in infrastructure to link agricultural areas to input and
output markets
Implications of Land Constraint Analysis
15

16. • Land (varies by region / agro-ecology)
• Labor (and rates of urbanization)
• Capital (and rates of investment by sector)
– Determined by domestic and foreign savings
– Private and public investment choices
• Technical change (changes in TFP)
Drivers of Agricultural and Economic Growth
16

17. Ethiopia: Agro-ecological Zones
17
Zone Classification Parameters
Elevation:
Highlands: >1500 meters
above sea level
Moisture Reliability:
Annual rainfall (mean/std)
>= 7.5
Cropping System:
Cereal or enset based
(moisture reliable
highlands only)
Drought Prone Lowland /
Pastoralist:
Mean annual rainfall <
500mmHighland moisture reliable zones accounted for 92% of
cereal area cultivated and production 2013/14.

18. Drivers of Agricultural Growth:
Land Constraints
The base simulation assumes slow area expansion (less than
1% per year) in the highlands.
18
Land Supply Growth 2017-35 (percent)
Base Urban Agric RNFE
National 0.64 0.64 0.85 0.64
Rural 0.64 0.64 0.85 0.64
R1: Dry Highlands 0.19 0.19 0.19 0.19
R2: Dry Lowlands 0.89 0.89 1.15 0.89
R3: Moist Lowlands 1.76 1.76 3.50 1.76
R4: Moist High Cereals 0.73 0.73 0.73 0.73
R5: Moist High-Enset 0.25 0.25 0.25 0.25

19. Growth Rates by Region
Growth Rates of Cities by
Initial Period City Category
1984-94 1994-07 2007-15 1984-94 1994-07 2007-15
Addis Ababa 5.16% 3.30% 2.25% 5.16% 3.30% 2.25%
Cities 100-500k - 19.25% 9.76% - 6.31% 5.09%
Cities 50-99k 1.76% 3.37% 8.09% 5.37% 6.78% 6.15%
Cities/Towns 20-49k 15.08% 7.07% 6.30% 4.81% 5.29% 5.74%
Other Urban 4.24% 5.62% 1.99%
Total Urban 6.15% 6.21% 4.60%
Rural 3.40% 3.74% 2.09%
Total Population 3.74% 4.10% 2.52%
Drivers of Growth: Urbanization
Overall, medium size cities are growing at 5-6% per year.
19
Source: Calculated from CSA data (various years).

20. Drivers of Growth: Foreign Capital Inflows
Source: IMF (various years). (2016/17 figures are projections.)
0
2
4
6
8
10
12
14
16
18
20
2004/05 2006/07 2008/09 2010/11 2012/13 2014/15 2016/17
billionUS$
Foreign Capital Inflows Foreign Direct Investment Public Transfers
Net Servs + Priv Transfers Exports
Imports
21
Balance of Payments: 2004/05 to 2016/17
• Total imports of goods in
2016/17 (US$ 18.0 bn)
were 2.2 times their level
of 2004/05.
• Foreign capital inflows,
private transfers and
foreign direct investment
together were US$ 13.6
bn in 2016/17 (75.6 % of
the value of merchandise
imports).
• Merchandise exports
accounted for only 19.4%
of total foreign exchange
net inflows.
Foreign capital inflows have been large.
Projected debt/GDP for 2016/17 was 54.1%;
projected external debt/GDP was 30.5%.

21. Ethiopia: Composition of GDP 2010/11 and 2015/16
Source: CSA (2017).
• Agriculture’s share in GDP fell from 46.1 to 36.4 percent.
• Most (61.5%) of change in real GDP from agriculture, construction and trade.
0
100
200
300
400
500
600
700
800
GDP 2010/11 GDP 2015/16 Change in GDP 2010/11-15/16
(billion2010/11birr)
Agriculture Manufacturing Construction Other Industry
Trade Hotels, Restaurants Transport, Comm. Real Estate
Other Private Services Public Services
22

22. • Detailed economic structure
– 69 sectors split across 7 zones (2010/11 social accounting matrix)
• Addis Ababa | secondary cities >50k | five rural areas and towns <50k
– In each zone, rural/urban labor separated by education levels and
households separated by expenditure quintiles
• Model assumptions and behavior
– National product markets
– Population and labor (by zone) grow at different rates
– Total crop land (by zone) grows at fixed rates (individual crops’
areas are endogenously allocated)
– Foreign savings is exogenous; real exchange rate is endogenous
Ethiopia Economywide Model
23

23. 24
• Model captures agriculture’s contribution to the Agri-
Food System (AFS) and broader national economy
Ethiopia’s Agriculture-Food System
GDP Employment
National economy 100.0 100.0
Agriculture-food system 52.9 81.8
Agriculture (crops, livestock, etc.) 41.7 75.5
Agricultural processing (milling, etc.) 2.1 0.8
Farm/processing input production 1.2 0.5
Agricultural trade & transport 8.0 4.9
Share of total, 2010/11 (%)
Source: 2010/11 Social Accounting Matrix (SAM)

24. • Model run over the period 2010/11 - 2034/35
– 2010/11-2015/16 replicates observed trends
– 2016/17 onwards based on projections
• Four scenarios:
– Baseline: Business-as-usual
– Cities: Faster urbanization in cities >50k
– Agriculture: Greater investment in agriculture
– Rural Towns: Faster growth in rural nonfarm and towns <50k
25
Simulations

25. 26
Baseline Cities Agriculture Small towns
National population 2.0 2.0 2.0 2.0
Rural 1.4 1.0 1.4 1.5
Urban 4.1 5.1 4.1 3.9
Total GDP growth 7.1 8.6 7.9 8.1
Labor supply 1.8 1.6 1.8 1.8
Land supply 0.6 0.6 0.8 0.6
Capital accumulation 7.6 9.6 7.8 8.2
TFP growth 2.3 2.7 2.9 2.9
Foreign capital/GDP (%) 23.5 29.5 22.6 23.5
Total investment/GDP (%) 27.5 41.3 27.3 29.5
Model Results: Growth Drivers
Average annual growth rate, 2016/17-2034/35 (%)

26. 27
26.5
31.8
15.8
17.8
25.4
15.0
20.0
25.0
30.0
35.0
2010 2015 2020 2025 2030 2035
Urbanpopulationshare(%)
Baseline & Agriculture Cities Small towns
Projected Urbanization Rates

27. 28
• All scenarios accelerate AFS transformation
(i.e., faster growth in upstream/downstream sectors)
Agri-Food System Growth Outcomes
Baseline Cities Agriculture Small towns
National economy 7.1 8.6 7.9 8.1
Agriculture-food system 3.7 3.8 5.8 4.0
Agriculture 3.2 3.1 5.4 3.4
Agricultural processing 6.1 6.7 7.6 6.7
Farm/processing input production 6.0 6.4 8.0 6.5
Agricultural trade & transport 4.8 5.2 6.7 5.3
Average annual growth rate, 2016/17-2034/35 (%)

28. • All scenarios improve national household welfare
– Agriculture and small town scenarios narrow the rural-
urban divide
29
Household Welfare Outcomes
Per capita household consumption growth, 2016/17-2034/35 (%)
5.6 5.6
5.7
6.3
6.0
7.2
6.7 6.7 6.7
6.4
6.5
6.0
5.0
5.5
6.0
6.5
7.0
7.5
National Rural Urban
Averageannualgrowth
(%)
Baseline Cities Agriculture Small towns

29. • Agriculture and small town scenarios are more pro-
poor, despite slower national economic growth
30
Poor Household Outcomes
Per capita household consumption growth, 2016/17-2034/35 (%)
5.6
6.3
6.7
6.4
5.8
6.5
7.0
6.7
5.0
5.5
6.0
6.5
7.0
7.5
Baseline Cities Agriculture Small towns
Averageannualgrowth
(%)
All households Poor households (quintile 2)

30. • Agricultural growth will decelerate
– Growing land constraints only partly offset by cultivating
more of the moisture-sufficient lowlands
– Urbanization reduces rural labor force, despite continued
rural population growth
– Agriculture remains most effective at reducing poverty
• The Agri-Food System expands as farming’s
importance declines
– Small towns may be more effective at promoting
continued rural development, despite smaller national
benefits for national economic growth and urban welfare
31
Summary

31. • Refinement of parameters and baseline assumptions
(construction of 2015/16 SAM?)
• New simulations with variations on productivity
growth and migration by commodity and region
• Sensitivity analysis
• Synthesis of overall results
Future Analysis (Next Steps)
32